Dissecting autoimmune cellular and molecular networks in vitiligo

摘要：白癜风是一种毁容的器官特异性自身免疫性疾病，影响世界1%的人口， 其中仅在美国就有300万人。目前还没有FDA批准的治疗白癜风的药物，而且 目前的一线治疗效果不明显。 是什么控制了白癜风的传播？为什么它的进展速度在患者之间是不同的？这些 都是知之甚少的问题。在这个项目中，我们试图提供解释 这些基本问题。我们的范式转换假说是炎症性和非传染性之间的平衡 直接在皮肤内的耐受通路决定了病变的位置及其进展速度。 因此，局部皮肤变化是白癜风进展的核心。 我们建议使用技术进步来测试和扩展我们的假设，这些技术进步现在才使这成为可能。 首先，我们开发了一种吸泡方法，可以对组织渗透的免疫细胞进行强有力的采样。 而不会混淆炎症和水泡本身。第二，我们建立了单细胞RNA-Seq (单链RNA-序列)方法，并已成功地将其应用于水泡液体样本。第三，我们建议 开发GridRNA-Seq，其中我们使用激光显微切割白癜风皮损的切面活检组织成网格 小的组织立方体，每个包含10-20个细胞，代表三维组织结构。然后我们 使用低输入RNA-Seq协议来分析每个立方体的表达水平。 这三种技术的结合使我们处于从根本上改变我们的方法的独特地位 来研究白癜风。利用scRNA-Seq，我们将发现白癜风皮损中存在的细胞类型，并编译基因 每个单元格的表达式签名。使用配体/受体分析，我们将建立细胞信号 支持疾病发展模型的网络。通过比较皮损和非皮损水泡样本，我们 将识别白癜风的异常信号，特别是耐受性和炎症信号的不同 在皮损和非皮损皮肤之间。尽管功能强大，scRNA-Seq对细胞混合物进行了测序，但其起源 的细胞都丢失了。为了解决这一限制，我们将开发GridRNA-Seq来描述10-20个细胞的“块” 从皮肤上一个已知的分界区域。网格中的每个区块都有一个很好的表型，如 根据块所在位置的组织学外观确定。通过集成特定类型的细胞 使用来自GridRNA-Seq的批量RNA-Seq数据的签名我们建议对这种混合表达数据进行去卷积 以估计每个区块的细胞组成及其表达。然后，我们将使用此信息来 与疾病表型相关的特异性表达和细胞类型组成变化。总而言之，我们的 数据将直接评估单个细胞的确切耐受性和炎症平衡及其相关性 疾病表型，因此两者都验证了我们最初的假设，并提供了一个公正的观点 白癜风在个体细胞水平上的发病机制。

Abstract: Vitiligo is a disfiguring organ-specific autoimmune disease that affects 1% of the world population, including 3 million individuals in the U.S. alone. There are no FDA-approved medical treatments for vitiligo, and current first-line therapies have marginal efficacy. What controls the spreading of vitiligo? Why is its rate of progression different from patient to patient? These are poorly understood problems. In this project we seek to provide the molecular mechanism that explains these fundamental questions. Our paradigm-shifting hypothesis is that the balance between inflammatory and tolerogenic pathways directly within the skin determines the location of lesions and their rate of progression. Thus, local changes in skin are at the core of vitiligo progression. We propose to test and expand our hypothesis using technological advances that only now make this possible. First, we developed a suction blistering method that provides robust sampling of tissue-infiltrating immune cells without confounding inflammation from blistering itself. Second, we have established a single cell RNA-Seq (scRNA-Seq) methodology and have successfully applied it to blister fluid samples. Third, we propose to develop gridRNA-Seq where we use laser microdissection of incisional biopsies of vitiligo lesions into grids of small cubes of tissue containing 10-20 cells each, representing the three dimensional tissue structure. We then use a low input RNA-Seq protocol to profile the expression level of each cube. The combination of these three technologies put us in a unique position to fundamentally change our approach to study vitiligo. With scRNA-Seq we will find the cell types present within vitiligo lesions and compile gene expression signatures for each of these cells. Using ligand/receptor analysis we will build cell signaling networks to support models of disease progression. By comparing lesional with nonlesional blister samples we will identify aberrant signaling in vitiligo, and in particular how tolerogenic and inflammatory signals differ between lesions and nonlesional skin. Although powerful, scRNA-Seq sequences a cell mixture, and the origin of the cells is lost. To address this limitation, we will develop gridRNA-Seq to profile a “block” of 10-20 cells from a known, demarcated region in the skin. Each block in the grid has a well-characterized phenotype as established by the histological appearance at the location of the block. By integrating cell type specific signatures with bulk RNA-Seq data from gridRNA-Seq we propose to “deconvolve” this mixed expression data to estimate the cell composition of each block as well as its expression. We will then use this information to correlate specific expression and cell type composition changes with disease phenotype. Taken together, our data will directly assess the exact tolerogenic and inflammatory balance of individual cells and its association with disease phenotype and hence both test our original hypothesis as well as provide an unbiased view of vitiligo pathogenesis at the individual cell level.